Hi Petri,

I happen to think that MC is the most human like approach currently
being tried.  

The reason I say that is that humans DO estimate their winning chances
and "tally" methods, where you simply tally up features/weights
(regardless of how sophisticated)  is not how strong humans think about
the game. 

Also, the best first global game tree approach, whatever you call it
such as UCT and others,  is a very close model of how humans play the
game too.    We may notice 3 moves that look playable, but gradually
come to focus on just 2 of those.   Essentially monte carlo does this
too.    Very narrow focused trees.    

The play-out portion is a crude approximation for imagination.   We
basically look at a board and imagine the final position.    The MC
play-outs kill the dead groups in a reasonably accurate (but fuzzy) way
and put the flesh on the skeleton.      Near the end of the game,  the
play-outs end mostly the same the way the game itself would end - and
the same way a human would expect it to look like.

I attribute the success of MC to the fact that it's the best simulation
of how WE do it.    The other approaches are clearly more synthetic,
including raw MC without a proper tree.

- Don


Petri Pitkanen wrote:
> 2007/12/11, terry mcintyre <[EMAIL PROTECTED]>:
>   
>> With Go, there are many situations which can be read out precisely, provided
>> that one has the proper tools - ladders, the ability to distinguish between
>> one and two eyes; the ability to reduce eyespaces to a single eye with an
>> appropriate placement; and so forth. Failure to recognize such situations is
>> like failing to spot a pinned piece or a passed pawn.
>>
>>     
>
> I am no fan on MC approach but basically MC can read L&D given enough
> of simulations. It will read them without knowing that they need to be
> analysed. Point in MC being that once you get more power you get
> better L&D as well, but without extra coding.
>
> This approach will result in non-human like game BUT likewise chess
> programs did not get strong by emulating humans. They just took one
> simple thing humans do and took it to extreme. Whatever approach will
> do the trick in go it will be similar in this sense.
>
>   
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